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Course on 'Introduction to Mathematical Oncology'
Course on Medical Image Processing
Course on Introduction to Mathematical
Instructors: M. Kohandel, S. Sivaloganathan
Description of the course:
This course will involve biology and clinical aspects of cancer,
and will also present an overview of recent mathematical models
developed to examine different stages of cancer growth and therapeutic
strategies. It is basically designed as a course for graduate
students (not for credit) who are interested
in working in the area of cancer modeling and related treatment
Lecture Times and Course Outline:
(The first hour of each lecture will cover the biology aspects,
while the second half will consist of related mathematical modeling).
Introduction to cancer biology and mathematical oncology
Metastasis and invasion
|Lecture 5: LAST LECTURE
Cancer stem cells
- Cancer Biology (R. Weinberg)
- The Basic Science of Oncology (Tannock et al.)
- Mathematical Biology (J. D Murray)
- Cancer Modeling and Simulation (edited by L. Preziosi)
- Computational Biology of Cancer (D. Wodarz and N. Komarova)
- Some parts of lectures will be based on review and recent articles
Course on Medical Image Processing*
Instructors: C. Drapaca, J. Trzasko, C. Studholme, H. Zhu, Y.
Schedule of the course:
11:00 am to 1:30 pm, with 30 min for lunch from 12:00 pm to
All lectures will be held at the Fields Institute.
Description of the course:
Tumors, and in particular cancer, can be difficult to detect,
diagnose and treat. Digital imaging techniques, computer aided
diagnosis, image-guided surgery and drug treatment can improve
the accuracy and efficiency of tumors detection, diagnosis and
treatment. Therefore computer assisted techniques have become
a valuable component in today's clinical research and practices.
This graduate course on image processing and treatment planning
is a collection of feature lecture series, focusing on IMRT inverse
treatment planning, CT, MR image reconstruction and various means
of analyzing and processing images including image co-registration,
level sets, and time-frequency analysis, etc.
The course will cover the following topics:
1. Convex and robust optimization techniques for radiotherapy
2. Time-frequency analysis and level set methods for imaging sciences.
3. Imaging physics, contemporary methods for fast imaging, image
registration and brain image analysis.
In addition, Dr. Zinchenko's seminar on August 22 th will be a
MATLAB tutorial on optimization software, (in particular, SeDuMi
*This course is not for credit.
Apply to the Program:
All scientific events are open to the mathematical sciences community.
Visitors who are interested in office space or funding are
requested to apply by filling out the application
Additional support is available (pending NSF funding) to support
junior US visitors to this program. Fields scientific programs are
devoted to research in the mathematical sciences, and enhanced graduate
and post-doctoral training opportunities. Part of the mandate of
the Institute is to broaden and enlarge the community, and to encourage
the participation of women and members of visible minority groups
in our scientific programs.
For additional information contact thematic(PUT_AT_SIGN_HERE)fields.utoronto.ca
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